Skip to content

[Core] Sharded State Loader download from HF #4889

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
ywang96 merged 3 commits into from
May 20, 2024
Merged

[Core] Sharded State Loader download from HF #4889

Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
4753e94
add hf download to sharded state loader
aurickq May 17, 2024
05e280c
update
aurickq May 17, 2024
b558b16
fix formatting
aurickq May 20, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
16 changes: 15 additions & 1 deletion vllm/model_executor/model_loader/loader.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -422,6 +422,16 @@ def get_end_ptr(tensor: torch.Tensor) -> int:
result[k] = t
return result

def _prepare_weights(self, model_name_or_path: str,
revision: Optional[str]):
if os.path.isdir(model_name_or_path):
return model_name_or_path
else:
allow_patterns = ["*.safetensors"]
return download_weights_from_hf(model_name_or_path,
self.load_config.download_dir,
allow_patterns, revision)
Comment thread
ywang96 marked this conversation as resolved.

def load_model(self, *, model_config: ModelConfig,
device_config: DeviceConfig,
lora_config: Optional[LoRAConfig],
Expand All @@ -432,14 +442,18 @@ def load_model(self, *, model_config: ModelConfig,
from safetensors.torch import safe_open

from vllm.distributed import get_tensor_model_parallel_rank

local_model_path = self._prepare_weights(model_config.model,
model_config.revision)

with set_default_torch_dtype(model_config.dtype):
with torch.device(device_config.device):
model = _initialize_model(model_config, self.load_config,
lora_config, vision_language_config,
cache_config)
rank = get_tensor_model_parallel_rank()
pattern = os.path.join(
model_config.model,
local_model_path,
self.pattern.format(rank=rank, part="*"),
)
filepaths = glob.glob(pattern)
Expand Down